5/30/2023 0 Comments Netlogo shapes![]() ![]() lead a team and rolled out two variants of telemedicine solutions for use by national populace of India, mitigating the Impact of Covid-19. believed that smokers might be at a higher risk. performed a quality assessment of multiple mobile applications (APPs) to evaluate their effects Speth et al. found the staggering patterns of inequitable mortality by race and ethnicity for US big cities Davalbhakta et al. developed guidelines that can mitigate its impact on health care Coltrain et al. found that SPA facilities can be proper settings of respiratory rehabilitations, for those post-pandemic patients Chowdhry et al. analyzed several potential iatrogenic causes of the detrimental effects on children and highlighted the risks under sudden changes of clinical practice Antonelli et al. Attention has also been paid to humanity aspects under the pandemic, such as societal impacts, information dissemination, health care, and technology. ![]() ![]() studied COVID-19 infection risk through high-dose immunoglobulin pulse therapy. evaluated 63 samples of concentrated plasma (CP) from New York Blood Center (NYBC) using side flow analysis (LFA) platform and Prada et al. proposed ‘Primed’ Mesenchymal Stem Cells (MSCs) as a therapeutic alternative Ragnesola et al. analyzed non-chemical signals of biological elements, a unique biophysical feature of COVID-19 Raza et al. Revealing characteristics and developing treatments become a core task for global scientists and studies such as pathology analysis, patient treatments and influences have been done. It greatly threatens global public health, with 178,837,204 infected and 3,880,450 died worldwide, by June 23th of 2021. The COVID-19 was first discovered in December, 2019, and declared a global pandemic by WHO on March 11st of 2020. It facilitates public administrations and social governance. Based on our model, it is feasible to model, calculate, and even predict evolutionary dynamics and life cycles trends of online collective actions. Therefore, our Agent-Based Modeling well grasps the micro-level mechanisms of real-world individuals (netizens), based on which we can predict individual behaviors of netizens and big data trends of specific online events. According to multiple criteria (spans, peaks, ratios, and distributions), the fitness between simulations and real big data has been substantially supported. Simulation outcomes well match the real big data of life cycle trends, and validity and robustness can be achieved. Under the optimal solutions, we repeated simulations by ten times, and took the mean values as robust outcomes. Based on multiple simulations and parametric traversal, we obtained the optimal parameter solution. We set two kinds of movable agents, Hots (events) and Netizens (individuals), which behave smartly and autonomously. We collected 138 related online events with macro-level big data characteristics, and used Agent-Based Modeling to capture micro-level individual behaviors of netizens. Based on the life cycle law, focusing on the life cycle process of COVID-19 online collective actions, we carried out both macro-level analysis (big data mining) and micro-level behaviors (Agent-Based Modeling) on pandemic-related online collective actions. The outbreak of COVID-19 has greatly threatened global public health and produced social problems, which includes relative online collective actions. ![]()
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